16 citations · 16 across the 1 of their papers we have counts for
2 papers
cs.CG2020★ 16 cited
Optimizing persistent homology based functions
Mathieu Carrière, Frédéric Chazal, Marc Glisse +2
Solving optimization tasks based on functions and losses with a topological flavor is a very active, growing field of research in data science and Topological Data Analysis, with a…
cs.CV2017
Newton-type Methods for Inference in Higher-Order Markov Random Fields
Hariprasad Kannan, Nikos Komodakis, Nikos Paragios
Linear programming relaxations are central to {\sc map} inference in discrete Markov Random Fields. The ability to properly solve the Lagrangian dual is a critical component of suc…